This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.
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From the course by University of Maryland, College Park
Dealing With Missing Data
University of Maryland, College Park
Course 5 of 7 in the Specialization Survey Data Collection and Analytics
From the lesson
Implementing the Steps
Software is critical to implementing the steps, but the R system is an excellent source of free routines. This module covers several R packages, including sampling, survey, and PracTools that will select samples and compute weights.
Meet the Instructors
Richard Valliant, Ph.D.Research Professor
Joint Program in Survey Methodology
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